SI Table 5: SI-5 Site Counts

28 March, 2018

Get data ready:

library(toxEval)
library(dplyr)
library(tidyr)
library(DT)

path_to_tox <-  system.file("extdata", package="toxEval")
file_name <- "OWC_data_fromSup.xlsx"
full_path <- file.path(path_to_tox, file_name)

tox_list <- create_toxEval(full_path)

ACClong <- get_ACC(tox_list$chem_info$CAS)
ACClong <- remove_flags(ACClong)

cleaned_ep <- clean_endPoint_info(endPointInfo)
filtered_ep <- filter_groups(cleaned_ep)

chemicalSummary <- get_chemical_summary(tox_list, ACClong, filtered_ep)

#Trim some names:
levels(chemicalSummary$Class)[levels(chemicalSummary$Class) == "Antimicrobial Disinfectants"] <- "Antimicrobial"
levels(chemicalSummary$Class)[levels(chemicalSummary$Class) == "Detergent Metabolites"] <- "Detergent"
levels(chemicalSummary$Class)[levels(chemicalSummary$Class) == "Flavors and Fragrances"] <- "Flavor/Fragrance"


file_name <- "AOP_crosswalk.csv"
full_path <- file.path(path_to_tox, file_name)

AOP_crosswalk <- read.csv(full_path, stringsAsFactors = FALSE)
  
chemicalSummary <- chemicalSummary %>%
  left_join(select(endPointInfo, 
                   endPoint=assay_component_endpoint_name,
                   subFamily=intended_target_family_sub,
                   gene_symbol=intended_target_gene_symbol), by="endPoint") %>%
  left_join(select(tox_list$chem_info, CAS, `Chemical Name`), by="CAS")

Site tables:

tableData <- chemicalSummary %>%
    rename(Chemical=`Chemical Name`,
           Family=Bio_category) %>%
    group_by(site, endPoint, Family, subFamily, gene_symbol, Chemical) 
    
max_Samples <- tableData %>%
    summarize(sumEAR = sum(EAR)) %>% #Sum per date
    slice(which.max(sumEAR)) %>% # Gets max per date
    filter(sumEAR > 0) %>%
    data.frame() %>%
    spread(Chemical, sumEAR) %>%
    arrange(site, Family, subFamily, gene_symbol) %>%
    select(site, Family, subFamily, gene_symbol,endPoint, everything()) %>%
    mutate(maxSample = rowSums(.[-1:-5], na.rm = TRUE)) %>%
    select(site, Family, subFamily, gene_symbol, endPoint, maxSample)
  
tableData <- tableData %>%
    summarize(maxEAR = max(EAR)) %>%
    filter(maxEAR > 0) %>%
    data.frame() %>%
    spread(Chemical, maxEAR) %>%
    arrange(site, Family, subFamily, gene_symbol) %>%
    select(site, Family, subFamily, gene_symbol,endPoint, everything()) %>%
  left_join(select(AOP_crosswalk,
                   endPoint=Component.Endpoint.Name,
                   AOP_id = AOP..,
                   AOP_title = AOP.Title), by="endPoint") %>%
    left_join(max_Samples, by=c("site", "Family", "subFamily", "gene_symbol","endPoint")) %>%
    select(site, Family, subFamily, gene_symbol, endPoint, AOP_id, AOP_title, maxSample, everything()) 

list_tables <- list()
chem_site <- tox_list$chem_site

for(i in 1:nrow(chem_site)){
  
  site <- chem_site$SiteID[i]
  site_name <- chem_site$`Short Name`[i]
  tableData_site <- tableData[tableData$site == site,]
  tableData_site <- Filter(function(x)!all(is.na(x)), tableData_site)

  list_tables[[2*i-1]] <- htmltools::tags$h3(site_name)
    
  if(nrow(tableData_site) > 0){
    tableData2 <- select(tableData_site, -endPoint, -Family, -subFamily, -gene_symbol, -AOP_id, -AOP_title, -site, -maxSample)
    tableData_site$nChems <- apply(tableData2, MARGIN = 1, function(x) sum(x>0, na.rm = TRUE))
    orderedCols <- tox_list$chem_info$`Chemical Name`[tox_list$chem_info$`Chemical Name` %in% names(tableData_site)]
    
    tableData_site <- tableData_site[,c("Family", "subFamily", "gene_symbol", "endPoint","AOP_id","AOP_title", "maxSample", "nChems", orderedCols)] 
    
    dt_table <- datatable(tableData_site, rownames = FALSE,extensions = 'Buttons',
                          options = list(dom = 'Bfrtip',
                                         
                                         buttons = list('colvis', list(
                                                       extend = 'collection',
                                                       buttons = list(list(extend='csv',
                                                                           filename = 'siteTable'),
                                                                      list(extend='excel',
                                                                           filename = 'siteTable'),
                                                                      list(extend='pdf',
                                                                           filename= 'siteTable')),
                                                       text = 'Download')
                                                     ))) %>%
                 formatSignif(columns=c("maxSample",orderedCols), digits=3)  
    
    list_tables[[2*i]] <- dt_table
  } else {
    list_tables[[2*i]] <- htmltools::tags$h3("EAR never > 0")
  }
}
htmltools::tagList(
  list_tables
)

StLouis

Nemadji

EAR never > 0

Bad

EAR never > 0

WhiteWI

EAR never > 0

Montreal

EAR never > 0

PresqueIsle

EAR never > 0

Ontonagon

Sturgeon

Tahquamenon

EAR never > 0

Manistique

EAR never > 0

Escanaba

EAR never > 0

Ford

EAR never > 0

Menominee

Peshtigo

Oconto

EAR never > 0

Fox

Manitowoc

Milwaukee

IndianaHC

Burns

StJoseph

PawPaw

Kalamazoo

GrandMI

Muskegon

WhiteMI

PereMarquette

EAR never > 0

Manistee

EAR never > 0

Indian

Cheboygan

ThunderBay

EAR never > 0

AuSable

Rifle

Saginaw

BlackMI

Clinton

Rouge

HuronMI

Raisin

Maumee

Portage

Sandusky

HuronOH

Vermilion

BlackOH

Rocky

Cuyahoga

GrandOH

Cattaraugus

Tonawanda

Genesee

Oswego

BlackNY

EAR never > 0

Oswegatchie

EAR never > 0

Grass

EAR never > 0

Raquette

EAR never > 0

StRegis